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Comprehensive automatisation de scripts Tools for Every Need

Get access to automatisation de scripts solutions that address multiple requirements. One-stop resources for streamlined workflows.

automatisation de scripts

  • AI Shell Agent

    AI Shell Agent is a CLI tool integrating LLMs into your terminal to generate commands, troubleshoot code, and automate tasks.
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    What is AI Shell Agent?
    AI Shell Agent is an open-source command line interface tool that embeds AI capabilities directly into your shell environment. It connects to large language models like OpenAI GPT, allowing you to ask natural language questions and receive shell commands as answers. The agent can generate new commands, modify existing scripts, debug errors, and provide usage examples for unfamiliar commands. It also accesses your current working directory context by reading files and command history. Users can configure prompts, select models, and define custom actions. Installation is straightforward with pip supporting Bash, Zsh, and Fish. Whether you're a developer needing quick code snippets, a sysadmin automating deployments, or a power user exploring AI in CLI, AI Shell Agent simplifies terminal-based tasks and workflows.
    AI Shell Agent Core Features
    • Natural language to shell command translation
    • Context-aware command suggestions based on history
    • Script generation and modification
    • Error debugging and solution proposals
    • File reading and writing through AI instructions
    • Customizable prompts and model selection
    AI Shell Agent Pro & Cons

    The Cons

    AI Code Copilot (aider integration) is experimental and may be less intuitive or stable.
    Requires Python 3.11+ and some manual setup/configuration which might be challenging for non-technical users.
    No direct pricing or commercial offering provided; likely fully open source but lacks paid support or hosted service.
    No mobile or browser app availability; limited to command-line interface.
    Potential risks if HITL safety checks are bypassed or misunderstood.

    The Pros

    Modular and extensible toolsets for terminal, file management, AI code copiloting.
    Human-in-the-Loop (HITL) safety confirmations for critical operations to prevent unintentional damage.
    Supports multiple AI models including OpenAI and Google AI with configurable API keys.
    Cross-platform compatibility for Windows, Linux, and macOS with OS-specific context guidance.
    Maintains conversation context with persistent chat sessions and per-chat configurations.
    Experimental AI-powered code editing integration with aider-chat for advanced file manipulation.
    Multi-language UI support and automated localization via AI.
    Open source with active development and modular architecture.

  • Illufly

    Illufly is an AI storyboarding agent converting scripts into illustrated slide decks using GPT-driven narratives and AI image generation.
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    What is Illufly?
    Illufly is an AI-powered storyboarding platform designed to automate the creation of visual narratives. Users input a script, outline, or story summary; the agent segments it into scenes, generates descriptive narratives via GPT, and produces corresponding high-quality images through Stable Diffusion or Midjourney APIs. It then compiles these elements into a structured slide deck with customizable layouts, allowing users to review, edit, and export final storyboards as PDF or PPT files. Illufly streamlines the entire script-to-presentation workflow for creators across industries.

  • Python Coding Agent

    An AI-powered Python coding agent that generates, executes, and debugs Python code from natural language prompts.
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    What is Python Coding Agent?
    Python Coding Agent is an open-source command-line tool that uses GPT models to generate Python code based on text prompts, execute that code locally, and catch runtime errors. It provides instant feedback, allowing users to iteratively refine code, automate repetitive scripting tasks, prototype data analysis pipelines, and debug functions. By combining natural language understanding with real-time code execution, it bridges the gap between idea and implementation, speeding up development and learning.
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